ArtsAutosBooksBusinessEducationEntertainmentFamilyFashionFoodGamesGenderHealthHolidaysHomeHubPagesPersonal FinancePetsPoliticsReligionSportsTechnologyTravel

Hypothesis Testing Model

Updated on October 25, 2014

Hypothesis Testing Model

Hypothesis testing is used by researchers in a variety of quantitative research studies to prove or disprove a theory. Hypothesis testing is a “procedure for deciding whether the outcome of a study (results for a sample) supports a particular theory or practical innovation” (Aron, Coups, & Aron, 2013, p. 108). There are five main steps for organizing hypothesis testing: restate the question as a research hypothesis and a null hypothesis about the populations, determine the characteristics of the comparison distribution, determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected, determine the sample’s score on the comparison distribution, and decide whether to reject the null hypothesis.

The first step for organizing a hypothesis test is to restate the question as a research hypothesis and a null hypothesis about the populations. The research hypothesis is a “statement in hypothesis testing about the predicted relation between populations” (Aron, Coups, & Aron, 2013, p. 111). The null hypothesis is a “statement about a relation between populations that is the opposite of the research hypothesis” (Aron, Coups, & Aron, 2013, p. 111). The second step is to determine the characteristics of the comparison distribution; comparison distribution represents the population situation if the null hypothesis were to be proven correct (Aron, Coups, & Aron, 2013, p. 112). During this step the comparison distribution is compared with the score that came from the results of the sample. The third step is to determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected; the cutoff sample score, also known as the critical value, is the “point in hypothesis testing, on the comparison distribution at which, if reached or exceeded by the sample score, you reject the null hypothesis” (Aron, Coups, & Aron, 2013, p. 112). During this step researchers decide how extreme a score must be for the score to be too implausible for the null hypothesis to be true. The fourth step is to determine the sample’s score on the comparison distribution; this is the step where the study is carried out, the results of the sample are collected, and the z-score for the sample’s raw score is determined based on the standard deviation of the comparison distribution and the population mean (Aron, Coups, & Aron, 2013, p. 114). The fifth and final step is to decide whether to reject the null hypothesis; this is done by comparing the sample’s Z score to the cutoff Z score in order to decide if the null hypothesis is accepted or rejected.

Hypothesis testing is mainly used by researchers in order to determine if a theory or hypothesis is accurate or inaccurate through statistical testing. The five step model of hypothesis testing has the advantage of: being simple to calculate, working with most quanataive research, being suited for comparisons, and providing provable rational results that decisively reject or accept the research hypothesis and the null hypothesis about the population.

Reference

Aron, A., Aron. E., Coups. E. (2014). Statistics for Psychology Pearson Education Inc. 2014.

Chapter 11: Correlation

Correlation

Association between scores on two variables

e.g., age and coordination skills in children, price and quality

Graphing Correlations
The Scatter Diagram

Steps for making a scatter diagram

1. Draw axes and assign variables to them

2. Determine range of values for each variable and mark on axes

3. Mark a dot for each person’s pair of scores

Graphing Correlations
The Scatter Diagram

Graphing Correlations: The Scatter Diagram

Patterns of Correlation

Linear correlation

Curvilinear correlation

No correlation

Positive correlation

Negative correlation

Degree of Linear Correlation
The Correlation Coefficient

Figure correlation using Z scores

Cross-product of Z scores

Multiply Z score on one variable by Z score on the other variable

Correlation coefficient

Average of the cross-products of Z scores

Degree of Linear Correlation
The Correlation Coefficient

General formula for the correlation coefficient:

Positive perfect correlation: r = +1

No correlation: r = 0

Negative perfect correlation: r = –1

Correlation and Causality

Three possible directions of causality:

1. X Y

2. X Y

3. Z

X Y

Correlation and Causality

Correlational research design

Correlation as a statistical procedure

Correlation as a research design

Issues in Interpreting the Correlation Coefficient

Statistical significance

Proportionate reduction in error

r2

Used to compare correlations

Restriction in range

Unreliability of measurement

Curvilinearity

Spearman’s rho

Power for Studies Using
Correlation Coefficient
(.05 significance level)

Table indicated below here

Approximate Sample Size for
80% Power for Correlation Studies (.05 significance level)

Table indicated below here

Correlation in Research Articles

Scatter diagrams occasionally shown

Correlation matrix

Comments

    0 of 8192 characters used
    Post Comment

    No comments yet.

    working

    This website uses cookies

    As a user in the EEA, your approval is needed on a few things. To provide a better website experience, hubpages.com uses cookies (and other similar technologies) and may collect, process, and share personal data. Please choose which areas of our service you consent to our doing so.

    For more information on managing or withdrawing consents and how we handle data, visit our Privacy Policy at: https://hubpages.com/privacy-policy#gdpr

    Show Details
    Necessary
    HubPages Device IDThis is used to identify particular browsers or devices when the access the service, and is used for security reasons.
    LoginThis is necessary to sign in to the HubPages Service.
    Google RecaptchaThis is used to prevent bots and spam. (Privacy Policy)
    AkismetThis is used to detect comment spam. (Privacy Policy)
    HubPages Google AnalyticsThis is used to provide data on traffic to our website, all personally identifyable data is anonymized. (Privacy Policy)
    HubPages Traffic PixelThis is used to collect data on traffic to articles and other pages on our site. Unless you are signed in to a HubPages account, all personally identifiable information is anonymized.
    Amazon Web ServicesThis is a cloud services platform that we used to host our service. (Privacy Policy)
    CloudflareThis is a cloud CDN service that we use to efficiently deliver files required for our service to operate such as javascript, cascading style sheets, images, and videos. (Privacy Policy)
    Google Hosted LibrariesJavascript software libraries such as jQuery are loaded at endpoints on the googleapis.com or gstatic.com domains, for performance and efficiency reasons. (Privacy Policy)
    Features
    Google Custom SearchThis is feature allows you to search the site. (Privacy Policy)
    Google MapsSome articles have Google Maps embedded in them. (Privacy Policy)
    Google ChartsThis is used to display charts and graphs on articles and the author center. (Privacy Policy)
    Google AdSense Host APIThis service allows you to sign up for or associate a Google AdSense account with HubPages, so that you can earn money from ads on your articles. No data is shared unless you engage with this feature. (Privacy Policy)
    Google YouTubeSome articles have YouTube videos embedded in them. (Privacy Policy)
    VimeoSome articles have Vimeo videos embedded in them. (Privacy Policy)
    PaypalThis is used for a registered author who enrolls in the HubPages Earnings program and requests to be paid via PayPal. No data is shared with Paypal unless you engage with this feature. (Privacy Policy)
    Facebook LoginYou can use this to streamline signing up for, or signing in to your Hubpages account. No data is shared with Facebook unless you engage with this feature. (Privacy Policy)
    MavenThis supports the Maven widget and search functionality. (Privacy Policy)
    Marketing
    Google AdSenseThis is an ad network. (Privacy Policy)
    Google DoubleClickGoogle provides ad serving technology and runs an ad network. (Privacy Policy)
    Index ExchangeThis is an ad network. (Privacy Policy)
    SovrnThis is an ad network. (Privacy Policy)
    Facebook AdsThis is an ad network. (Privacy Policy)
    Amazon Unified Ad MarketplaceThis is an ad network. (Privacy Policy)
    AppNexusThis is an ad network. (Privacy Policy)
    OpenxThis is an ad network. (Privacy Policy)
    Rubicon ProjectThis is an ad network. (Privacy Policy)
    TripleLiftThis is an ad network. (Privacy Policy)
    Say MediaWe partner with Say Media to deliver ad campaigns on our sites. (Privacy Policy)
    Remarketing PixelsWe may use remarketing pixels from advertising networks such as Google AdWords, Bing Ads, and Facebook in order to advertise the HubPages Service to people that have visited our sites.
    Conversion Tracking PixelsWe may use conversion tracking pixels from advertising networks such as Google AdWords, Bing Ads, and Facebook in order to identify when an advertisement has successfully resulted in the desired action, such as signing up for the HubPages Service or publishing an article on the HubPages Service.
    Statistics
    Author Google AnalyticsThis is used to provide traffic data and reports to the authors of articles on the HubPages Service. (Privacy Policy)
    ComscoreComScore is a media measurement and analytics company providing marketing data and analytics to enterprises, media and advertising agencies, and publishers. Non-consent will result in ComScore only processing obfuscated personal data. (Privacy Policy)
    Amazon Tracking PixelSome articles display amazon products as part of the Amazon Affiliate program, this pixel provides traffic statistics for those products (Privacy Policy)